AI Motion
Forklift Pedestrian Safety System
Forklift Pedestrian Detection & Automatic Slowdown & Stop

How AI Motion Works
AI Motion is a forklift pedestrian safety system developed by Quick Autopart. AI Motion detects pedestrians around a forklift using AI vision and automatically commands the vehicle to slow down or stop when a person enters a defined warning or danger zone. The system works with a Motion Controller to provide automatic speed control according to configurable safety zones.
AI Motion helps reduce collision risk in areas with blind spots, limited visibility, or pedestrian traffic. Using AI deep learning, the system distinguishes people from surrounding objects and sends slowdown or stop commands according to the configured detection zone.

Configurable Safety Zones & Speed Control
The AI camera provides a configurable detection range from 0.5 to 20 meters and supports three safety zones: green, yellow, and red. The size of each zone can be adjusted to suit different operating environments. When a pedestrian is detected, AI Motion sends commands to the Motion Controller to control forklift acceleration according to the settings assigned to each zone.
In the default configuration, acceleration is reduced to 40% when a pedestrian enters the yellow warning zone. When a pedestrian enters the red danger zone, the forklift is commanded to stop. Acceleration settings for each zone can be independently configured from 0% to 100% to suit different operating conditions.

Strong AI Algorithm
The AI algorithm is designed to detect pedestrians around the forklift, including situations where only part of a person is visible, such as an arm or leg. This helps improve pedestrian detection in areas with partial obstruction or limited visibility. The system can also receive software updates as the AI model is further developed.

Motion Controller: Automatic Speed Control & Stop
Motion Controller is developed by Quick Autopart Co., Ltd. as the vehicle control component of the AI Motion system. A Thai petty patent application has been filed for the Motion Controller, an automatic forklift speed control device designed to reduce collision risk. It receives detection signals from connected safety devices and converts them into forklift control commands.
With AI Motion, when a pedestrian is detected in a configured safety zone, the controller can limit forklift acceleration in the warning zone and command the forklift to stop in the danger zone. Each zone can be configured independently according to the operating environment.
The Motion Controller supports up to four signal inputs and can work with different detection technologies, including AI cameras, UWB, and ultrasonic sensors. The appropriate detection method can be selected according to the application—for example, AI vision for pedestrian detection, UWB for tag-based proximity detection, or ultrasonic sensing for short-range obstacle detection.
Operational Safety Without Sacrificing Productivity
When a pedestrian enters the yellow warning zone, AI Motion does not need to stop the forklift immediately. The Motion Controller can reduce acceleration to a predefined level, allowing the operator to continue working at a controlled speed. If the pedestrian moves into the red danger zone, the system commands the forklift to stop.
Unlike a simple warning-or-stop approach, AI Motion provides an intermediate reduced-speed response in the yellow zone. This allows the forklift to remain operational in lower-risk situations while providing an automatic stop response when the risk increases. Acceleration levels for each zone can be independently configured from 0% to 100% to suit different operating environments.

Automatic Stop Test
Key observation: The forklift remains in reverse gear throughout the test, as shown by the reverse light. No brake light is activated during the stopping sequence, confirming that the brake pedal is not being pressed. When the pedestrian enters the configured danger zone, AI Motion sends the stop command and the forklift decelerates to a complete stop automatically.
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